scholarly journals PID Control for Electric Vehicles Subject to Control and Speed Signal Constraints

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Amanda Danielle O. da S. Dantas ◽  
André Felipe O. de A. Dantas ◽  
João Tiago L. S. Campos ◽  
Domingos L. de Almeida Neto ◽  
Carlos Eduardo T. Dórea

A PID control for electric vehicles subject to input armature voltage and angular velocity signal constraints is proposed. A PID controller for a vehicle DC motor with a separately excited field winding considering the field current constant was tuned using controlled invariant set and multiparametric programming concepts to consider the physical motor constraints as angular velocity and input armature voltage. Additionally, the integral of the error, derivative of the error constraints, and λ were considered in the proposed algorithm as tuning parameters to analyze the DC motor dynamic behaviors. The results showed that the proposed algorithm can be used to generate control actions taking into account the armature voltage and angular velocity limits. Also, results demonstrate that a controller subject to constraints can improve the electric vehicle DC motor dynamic; and at the same time it protects the motor from overvoltage.

Author(s):  
Andrean George W

Abstract - Control and monitoring of the rotational speed of a wheel (DC motor) in a process system is very important role in the implementation of the industry. PWM control and monitoring for wheel rotational speed on a pair of DC motors uses computer interface devices where in the industry this is needed to facilitate operators in controlling and monitoring motor speed. In order to obtain the best controller, tuning the Integral Derifative (PID) controller parameter is done. In this tuning we can know the value of proportional gain (Kp), integral time (Ti) and derivative time (Td). The PID controller will give action to the DC motor control based on the error obtained, the desired DC motor rotation value is called the set point. LabVIEW software is used as a PE monitor, motor speed control. Keyword : LabView, Motor DC, Arduino, LabView, PID.


2014 ◽  
Vol 7 (3) ◽  
pp. 65-79
Author(s):  
Ibrahem S. Fatah

In this paper, a Proportional-Integral-Derivative (PID) controller of DC motor is designed by using particle swarm optimization (PSO) strategy for formative optimal PID controller tuning parameters. The proposed approach has superior feature, including easy implementation, stable convergence characteristics and very good computational performances efficiency. The DC Motor Scheduling PID-PSO controller is modeled in MATLAB environment. Comparing with conventional PID controller using Genetic Algorithm, the planned method is more proficient in improving the speed loop response stability, the steady state error is reduced, the rising time is perfected and the change of the required input do not affect the performances of driving motor with no overtaking.


In developed nations, industries are made to function at control engineering costs via the use of appropriate control schemes for dc motors. This paper introduces the role played by dc motors in industries thereby necessitating the analysis and performance validation of dc motor in Internal Model Control (IMC) scheme as against the Proportional– Integral–Derivative (PID) control schemes that is widely used in most industries. Theories on dc motor model, PID and IMC controller were detailed to paved the way for the methodical approach of getting specifications and transfer function for a typical dc motor (model RMCS-3011). Matlab/Simulink software was then used to tune the PID controller for the purpose of finding the values of PID gains that meets the design requirements to achieve best performance, thereby enabling the simulation of the PID controller. Using Matlab m-file environment, IMC controller transfer function was generated and simulated. The IMC controller transfer function aimed at achieving a unity gain that tracks the set-point was approximately realized. In the realization process, it was obvious that a filter is required. The aim of this work is to evaluate the performance of the IMC controller over PID controller. Simulated plots in Matlab-Simulink using the PID gains for the PID controller, and time constants and filter order for the IMC were presented. The quantitative results of the IMC method when compared with that of PID control provides a commendable performance. However, the performance in terms of rise time is small and preferred with the use of Matlab-Simulink tuned PID controller. Conclusively, IMC controller would be the preferred controller where the robustness and accuracy of the dc motor speed control counts more than faster response


2012 ◽  
Vol 466-467 ◽  
pp. 1246-1250 ◽  
Author(s):  
Bin Ma ◽  
Qing Bin Meng ◽  
Feng Yu ◽  
Zhong Hua Han ◽  
Chang Tao Wang

In this paper, a controller is designed based on improved fuzzy PID to solve the problem that the dc motor performance of speed and dynamic is poor when using the conventional PID controller for the lack of adaptive capacity of the controller parameters. The improved fuzzy control algorithm is used for the tuning of PID controller to get good speed performances, which automatically adjust the parameter of PID controller according to the motor speed. The simulation results show that the improved fuzzy PID control with the advantages of fast response, small overshoot and strong anti-interference capability can effectively improve the dynamic characteristics and steady state accuracy.


2012 ◽  
Vol 588-589 ◽  
pp. 1650-1653
Author(s):  
Yu Hao Qian

Based on the mathematical model of the brushless DC motor (BLDCM), a self-adaptive fuzzy PID controller is designed to achieve high-precision speed control of motor by adopting fuzzy control principle, simulation is conducted in MATLAB /SIMULINK, the result shows that the controller can work well with quick response, no overshoot output and high control precision, has strong robustness under the circumstances of various disturbances and parameter variations, whose static and dynamic performance with the self-adaptive fuzzy PID control are both better than conventional PID control.


Author(s):  
Magdi M. El-Saadawi ◽  
Eid Abdelbaqi Gouda ◽  
Mostafa A. Elhosseini ◽  
Mohamed Said Essa

This paper uses Fractional-order PID control (FOPID) to control the speed of the DC motor.  FOPID is more flexible and confident in controlling control higher-order systems compared to classical PID. In this work, the FOPID controller tuning is carried out using different methods ranging from classical techniques to most recent heuristic methods are Fractional Grey wolf Optimization and Nelder-Mead. Moreover, parameter estimation of real-world DC motor is carried out experimentally using Matlab/Simulink interfaced to an Arduino Uno board. The feasibility of FOPID is demonstrated through applications to well-known DC motor case study and the estimated DC motor. Based on ISE, ITE, and ISTE performance measures, the proposed approach provide less settling time, rise time and comparable overshoot compared with existing literature approaches. A robustness assessment with differences in the DC motor components is performed. Simulation finding provide validation of the suggested work and the FOPID controller effectiveness as compared to classical PID controller in terms of robustness and control effect.


Author(s):  
Salman Jasim Hammoodi ◽  
Kareem Sayegh Flayyih ◽  
Ahmed Refaat Hamad

<span>In this paper, we first write a description of the operation of DC motors taking into account which parameters the speed depends on thereof. The PID (Proportional-Integral-Derivative) controllers are then briefly described, and then applied to the motor speed control already described , that is, as an electronic controller (PID), which is often referred to as a DC motor. The closed loop speed control of a Brush DC motor is developed applying the well-known PID control algorithm. The objective of this work is to designed and simulate a new control system to keep the speed of the DC motor constant before variations of the load (disturbances), automatically depending to the PID controller. The system was designed and implementation by using MATLAB/SIMULINK and  DC motor.</span>


2014 ◽  
Vol 70 (3) ◽  
Author(s):  
Kumeresan A. Danapalasingam

Electric power-assisted steering (EPS) is a control system where an electric motor is used to provide assistance in vehicle steering. In this work controllers are designed for a column-type EPS equipped with a brushed DC motor to enable energy optimization. Using a mathematical model of EPS a controller is developed based on nonlinear adaptive regulation method to generate driver torque. PID control is then applied to produce assistance torque in accordance to desired energy saving. Simulation results using Matlab show the trade-off between driver’s comfort and energy consumption. The control paradigm introduced here fits appropriately in electric vehicles (EVs) where electrical energy is scarce.  


2011 ◽  
Vol 305 ◽  
pp. 173-176
Author(s):  
Jian Bo Cao ◽  
Ming Qiang Mao ◽  
Wan Lu Xu ◽  
Jia Ji ◽  
Jia Jiang ◽  
...  

To deal with the control problem of brushless DC motor (BLDCM), based on analyzing the work principle of BLDCM, the fuzzy-PID control was studied, and the fuzzy-PID controller of BLDCM was designed. The experimental results show that the fuzzy-PID controller is superior to the PID controller at steady-state tracking error. Additionally, the current and torque undulation of BLDCM were also improved.


Sign in / Sign up

Export Citation Format

Share Document